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Rift Valley Fever epidemiology, surveillance, and control: what have models contributed?

Version 2 2024-03-12, 12:11
Version 1 2023-10-18, 07:52
journal contribution
posted on 2024-03-12, 12:11 authored by Raphaëlle Métras, Lisa Collins, Richard G. White, Silvia Alonso, Véronique Chevalier, Christine Thuranira-McKeever, Dirk U. Pfeiffer
<p>Background: Rift Valley fever (RVF) is an emerging vector-borne zoonotic disease that represents a threat to human health, animal health, and livestock production, particularly in Africa. The epidemiology of RVF is not well understood, so that forecasting RVF outbreaks and carrying out efficient and timely control measures remains a challenge. Various epidemiological modeling tools have been used to increase knowledge on RVF epidemiology and to inform disease management policies.Aim: This narrative review gives an overview of modeling tools used to date to measure or model RVF risk in animals, and presents how they have contributed to increasing our understanding of RVF occurrence or informed RVF surveillance and control strategies.Methodology: Systematic literature searches were performed in PubMed and ISI Web of Knowledge. Additional research work was identified from other sources.Results: Literature was scarce. Research work was highly heterogeneous in methodology, level of complexity, geographic scale of approach, and geographical area of study. Gaps in knowledge and data were frequent, and uncertainty was not always explored. Spatial approaches were the most commonly utilized techniques and have been used at both local and continental scales, the latter leading to the implementation of an early warning system. Three articles using dynamic transmission models explored the potential of RVF endemicity. Risk factor studies identified water-related environmental risk factors associated with RVF occurrence in domestic livestock. Risk assessments identified importation of infected animals, contaminated products, or infected vectors as key risk pathways for the introduction of RVF virus into disease-free areas.Conclusions: Enhanced outbreak prediction and control and increased knowledge on RVF epidemiology would benefit from additional field data, continued development, and refinement of modeling techniques for exploring plausible disease transmission mechanisms and the impact of intervention strategies.</p>

History

School affiliated with

  • Department of Life Sciences (Research Outputs)

Publication Title

Vector-Borne and Zoonotic Diseases

Volume

11

Issue

6

Pages/Article Number

761-771

Publisher

Mary Ann Liebert for Society for Zoonotic Ecology and Epidemiology (SocZEE)

ISSN

1530-3667

eISSN

1557-7759

Date Submitted

2013-09-16

Date Accepted

2013-09-16

Date of First Publication

2013-09-16

Date of Final Publication

2013-09-16

ePrints ID

11921

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